Researchers in the medical field are employing AI algorithms to solve the challenges of processing large-scale, complex data to make new discoveries. One tool that stands out is AlgoraeOS, which aims to improve the process of identifying and approving new drugs. By supporting targeted drug repositioning, AlgoraeOS seeks to speed up and reduce costs in clinical trials. This involves exploring the potential applications of existing drugs for new therapeutic uses in treating a range of diseases.
The use of AI-driven drug discovery and development holds great promise for transforming the pharmaceutical industry. These algorithms can enhance analysis of clinical data, molecular structures, genetic information, and biological data to identify drug targets with greater precision and efficiency than traditional methods. Additionally, AI can streamline preclinical and clinical study design, significantly reducing time and costs associated with drug development.
In recent years, the preclinical stage of drug discovery has been time-consuming and costly, taking up to six years and billions of dollars. However, with AI tools like AlgoraeOS helping researchers reposition drugs for new uses or identify interactions between medications or toxicity issues. This not only guides them towards more promising areas of investigation but also does so at a lower cost compared to traditional methods. The collaboration between researchers leverages advanced AI models developed by A/Prof Vafaee’s team at her Biomedical AI Laboratory.